In logistics facilities, such as distribution centers or retail stores, goods are stored for retrieval by a pick worker or customer. Each type of item is known as a Stock Keeping Unit (SKU), and each SKU has a specific location in which it is kept. These items can be stored openly on shelving racks, or in compartmentalized containers, such as boxes or bins.
In a wholesale center, items are often stored in sealed cases, where individual units are packed together in a shipping case, as when they are received from a manufacturer. Cases may further be grouped together and stored on pallets, which is common for freight shipment of goods.
When goods need to be retrieved individually for order fulfillment or selection by a customer, they are typically stored individually and are not grouped into cases or pallets. The process of breaking the cases or pallets for individual product picking, that is, taking the individual pieces from the case or pallet and placing them in a specific storage location in a facility, is called put-away. The process of picking or selecting individual items from a specific storage location in a facility is known as piece-picking or each-picking. Put-away and piece-picking happens in both distribution warehouses and retail centers, whereas case-picking or pallet-picking typically only happens at a wholesale distribution center.
A fundamental problem with piece-picking, and to a lesser extent put-away, is that it is inherently time consuming; it requires a significant portion of time to be spent traveling from one item's storage location to another. For put-away, a person manually brings product cases to the pick locations and breaks them open to facilitate piece-picking. For piece-picking of a product, there is the added time it takes to find and identify the specific item of interest in its unique storage location. This is often accomplished by specific SKU numbers that positively identify the item to be picked. While different SKUs may appear to be the same, they may have some internal variations, such as weight, which cannot be identified outwardly. Finally, a person must manually pick or grasp the item and transfer it into a transport container, such as a cardboard box or plastic tote for shipping.
Due to the time consuming and very manual nature of piece-picking, it is a very costly process and, therefore, has received much attention by organizations looking to save time and money. There are many solutions for both optimizing and automating various aspects of piece-picking. Some techniques look to minimize the amount of travel time required to move from one point to another within a logistics facility by reorganizing the SKU locations such that the most frequently accessed items are grouped together or require a minimum amount of reach by a worker grasping the item.
Automation solutions range from augmenting manual labor with various technologies to completely replacing labor with customized picking equipment and infrastructure. For example, some automation systems support manual pick workers with barcode or radio frequency identification (RFID) scanners that enable them to more rapidly locate and identify a product. Others, such as voice picking technology, provide the pick workers with an audio and speech interface headset that communicates which items to pick and their location, thereby enabling a hands-free process that improves speed and productivity.
There are also many types of automated machines that enable more efficient picking operations. For example, large scale goods-to-person Automated Storage and Retrieval Systems (AS/RS) allow a pick worker to remain in a fixed location. These systems have movable SKU storage bins that can be carried by a machine to and from a fixed storage location and delivered to a worker for picking individual pieces out of the bins. There are also Automated Guided Vehicle (AGV) systems that can transfer storage racks to and from a pick area where a worker can locate and grab the requested item.
The automation equipment technologies presently available for picking operations require a substantial modification of infrastructure for the logistics center in which they are used. This requires a significant up-front investment from the facility, which may be difficult to afford and is the main reason such solutions have not been widely adopted. As such, many distribution facilities still rely on manual labor to accomplish piece-picking. Further, current automation systems are not viable for retail centers because the infrastructure must also be accessible to the customer. That is, current automation equipment cannot be used within a retail facility which relies on simple static shelving for product storage and display.
Currently, logistics facilities follow a standard process for put-away and picking of goods. Items arrive into the facility at a receiving area, typically in cases or pallets, and are commonly registered into an Inventory Management System (IMS) or Warehouse Management System (WMS). A WMS is a software database which stores information about SKUs which may include the product size, weight, inventory count, storage location, etc. After the items are received, they are put-away into their storage locations, typically open shelving or racks. This is usually a manual process which involves a stock worker physically moving the items to a location and transferring the items onto the shelf or rack.
Picking is done by a manual pick worker, also called selector or picker, in a warehouse, or by a customer in a retail facility. In a warehouse, picking happens after an order is received from an external customer. The orders are typically registered with the WMS, which then creates a work order, commonly known as a pick list, which instructs the picker which items must be retrieved, their quantities, and location within the facility. The picker then must find the items and physically transfer them to a shipping container that is associated with the order.
The two primary objections to automation for picking using currently known systems are: first, that the perceived upfront cost is too high, and second, that automation equipment is not flexible enough to accommodate changes to inventory or the operation process. As such, the majority of businesses have continued to rely on manual picking labor. The high cost and inflexibility of current automation is largely due to the infrastructure changes required for such solutions. Therefore, a solution that does not require changing significant infrastructure in a facility, such as using existing shelving and racks, and works side-by-side with manual labor is desired. Such a solution would reduce upfront cost and keep available the flexibility to use human workers.